Research resources


Introduction to Modern Statistics, an open source textbook with interactive R tutorials, by Mine Cetinkaya-Rundel and Johanna Hardin:

Fleas and Ticks

The CDC hub for tick info: University of Rhode Island’s comprehensive tick info site

TickTalk and TickReport Webinars from UMass

Tick collection and identification – SUBMIT YOUR DOG’S TICK HERE!

Get your Damminix Tick Tubes HERE

Are there tick-borne diseases of dogs in your area? Check the CAPC maps, here:

Grants, Funding, and Scientific Writing

UW Madison undergraduate research information:

UW Madison Writing Center: Offers free, non-credit workshops for undergrads, graduate and professional students, instructors, faculty, and academic staff. Workshops make it easy to learn and practice new and different approaches to writing—for a variety of writing situations. Browse the listings on their website or handy calendar.

UW Institute for Clinical and Translational Research (ICTR): Focused on research, education, and training in translational science, ICTR works with multiple schools at UW-Madison (including the SVM) to linked basic research to improvements in human health. There are many resources available through ICTR, including funding opportunities, clinical research resources, and a variety of training programs from videos and workshops to certificates to PhDs.

Want to Learn R?

Teacup Giraffes and Statistics: online learning modules for coding in R

“A delightful series of modules to learn statistics and R coding for students, scientists, and stats-enthusiasts.”

Recorded Live R for Data Science Classes, by Dr. Bharatendra Rai on YouTube.

Free online textbook R for Data Science

“This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.”

Free online self-paced course from Harvard: R Basics

“The first in our Professional Certificate Program in Data Science, this course will introduce you to the basics of R programming.”

Data Visualization

Data visualization resources, from the NCSU Library:

Textbooks and tutorials

Principles of Graphical Excellence, by Edward Tufte (from the Boston University School of Public Health):

Fundamentals of Data Visualization, by Claus Wilke:

How to know when to do what with your data

The Data Visualization Catalog:

From Data to Viz:

Software and tools for creating infographics (with some nice templates and examples)

Color palettes – Matches colors from uploaded images and gives you HEX codes – Find the best colors for maps

Presentations and videos on data visualization

The Science of Data Visualization

Larry Silverstein @ Tableau, 2018

The Beauty of Data Visualization

David McCandless @ TedEd, 2010

How Charts Lie: Getting smarter about data visualization

Alberto Cairo @ Demystifying Data Science, 2019

Data Visualization Literacy: Avoiding common mistakes and recognizing deceitful practices

Alberto Cairo @ Dana Farber Cancer Institute Data Science Zoominar,  2020

Other resources, including education/teaching focused material, can be found on my Teaching page.